{"id":"https://openalex.org/W2052340096","doi":"https://doi.org/10.1109/iri.2012.6303024","title":"Designing a rule-based hourly rainfall prediction model","display_name":"Designing a rule-based hourly rainfall prediction model","publication_year":2012,"publication_date":"2012-08-01","ids":{"openalex":"https://openalex.org/W2052340096","doi":"https://doi.org/10.1109/iri.2012.6303024","mag":"2052340096"},"language":"en","primary_location":{"id":"doi:10.1109/iri.2012.6303024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2012.6303024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 13th International Conference on Information Reuse & Integration (IRI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064772845","display_name":"Soo-Yeon Ji","orcid":"https://orcid.org/0000-0003-2677-2773"},"institutions":[{"id":"https://openalex.org/I324100","display_name":"Bowie State University","ror":"https://ror.org/0567w8j84","country_code":"US","type":"education","lineage":["https://openalex.org/I324100"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soo-Yeon Ji","raw_affiliation_strings":["Dept. of Computer Science, Bowie State University","Dept. of Computer Science, Bowie State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Bowie State University","institution_ids":["https://openalex.org/I324100"]},{"raw_affiliation_string":"Dept. of Computer Science, Bowie State University, USA","institution_ids":["https://openalex.org/I324100"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058077139","display_name":"Sharad Sharma","orcid":"https://orcid.org/0000-0001-7528-4616"},"institutions":[{"id":"https://openalex.org/I324100","display_name":"Bowie State University","ror":"https://ror.org/0567w8j84","country_code":"US","type":"education","lineage":["https://openalex.org/I324100"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharad Sharma","raw_affiliation_strings":["Dept. of Computer Science, Bowie State University","Dept. of Computer Science, Bowie State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Bowie State University","institution_ids":["https://openalex.org/I324100"]},{"raw_affiliation_string":"Dept. of Computer Science, Bowie State University, USA","institution_ids":["https://openalex.org/I324100"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071206125","display_name":"Byunggu Yu","orcid":"https://orcid.org/0000-0002-0732-6535"},"institutions":[{"id":"https://openalex.org/I174612323","display_name":"University of the District of Columbia","ror":"https://ror.org/037wegn60","country_code":"US","type":"education","lineage":["https://openalex.org/I174612323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byunggu Yu","raw_affiliation_strings":["Dept. of Computer Science & Information Technology, University of the District of Columbia","Dept. of Computer Science & Information Technology, University of the District of Columbia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Information Technology, University of the District of Columbia","institution_ids":["https://openalex.org/I174612323"]},{"raw_affiliation_string":"Dept. of Computer Science & Information Technology, University of the District of Columbia, USA","institution_ids":["https://openalex.org/I174612323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075876111","display_name":"Dong Hyun Jeong","orcid":"https://orcid.org/0000-0001-5271-293X"},"institutions":[{"id":"https://openalex.org/I174612323","display_name":"University of the District of Columbia","ror":"https://ror.org/037wegn60","country_code":"US","type":"education","lineage":["https://openalex.org/I174612323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Hyun Jeong","raw_affiliation_strings":["Dept. of Computer Science & Information Technology, University of the District of Columbia","Dept. of Computer Science & Information Technology, University of the District of Columbia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Information Technology, University of the District of Columbia","institution_ids":["https://openalex.org/I174612323"]},{"raw_affiliation_string":"Dept. of Computer Science & Information Technology, University of the District of Columbia, USA","institution_ids":["https://openalex.org/I174612323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.17554953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9678000211715698,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5297449827194214},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5054543018341064},{"id":"https://openalex.org/keywords/weather-prediction","display_name":"Weather prediction","score":0.4723159968852997},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.4383432865142822},{"id":"https://openalex.org/keywords/cart","display_name":"Cart","score":0.43442100286483765},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.4336879551410675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.356540322303772},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10041481256484985}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5297449827194214},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5054543018341064},{"id":"https://openalex.org/C2987469573","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather prediction","level":2,"score":0.4723159968852997},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4383432865142822},{"id":"https://openalex.org/C2777275308","wikidata":"https://www.wikidata.org/wiki/Q234668","display_name":"Cart","level":2,"score":0.43442100286483765},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.4336879551410675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.356540322303772},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10041481256484985},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iri.2012.6303024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2012.6303024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 13th International Conference on Information Reuse & Integration (IRI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W128754594","https://openalex.org/W1594031697","https://openalex.org/W1771933469","https://openalex.org/W1833977909","https://openalex.org/W1967610656","https://openalex.org/W1993030870","https://openalex.org/W2050827486","https://openalex.org/W2064151144","https://openalex.org/W2100273839","https://openalex.org/W2105594594","https://openalex.org/W2112081648","https://openalex.org/W2114039576","https://openalex.org/W2131824363","https://openalex.org/W2131966152","https://openalex.org/W2158638608","https://openalex.org/W2161042290","https://openalex.org/W2161180943","https://openalex.org/W2164603125","https://openalex.org/W2338837925","https://openalex.org/W4285719527","https://openalex.org/W6605241255","https://openalex.org/W6638593286","https://openalex.org/W7025534323"],"related_works":["https://openalex.org/W4400093351","https://openalex.org/W3193909393","https://openalex.org/W2322350723","https://openalex.org/W2618011907","https://openalex.org/W4226229889","https://openalex.org/W4318612353","https://openalex.org/W4389829534","https://openalex.org/W4400065455","https://openalex.org/W4390939596","https://openalex.org/W4392628570"],"abstract_inverted_index":{"Rainfall":[0],"prediction":[1,48,69,85,141],"is":[2,63,70,75,106,116],"important":[3,93],"in":[4],"many":[5],"aspects":[6],"of":[7,30,35,61,78,123,143,169],"our":[8],"economy":[9],"and":[10,52,108,114,125,131,135,149,153,171],"general":[11],"livelihood":[12],"by":[13],"preventing":[14],"any":[15,76],"serious":[16],"natural":[17],"disasters.":[18],"Although":[19],"numerous":[20],"methodologies":[21],"have":[22],"been":[23],"introduced":[24],"to":[25],"predict":[26],"hourly":[27,67,145,174],"rainfall,":[28],"most":[29],"them":[31],"cannot":[32],"provide":[33,90],"transparency":[34],"predicted":[36],"outcomes.":[37],"To":[38,54,98],"overcome":[39],"this":[40],"limitation,":[41],"we":[42,157],"propose":[43],"a":[44],"computer-aided":[45],"rule-based":[46],"rainfall":[47,57,68,84,146],"model":[49],"using":[50],"CART":[51,130,148],"C4.5.":[53],"correctly":[55],"perform":[56],"prediction,":[58],"the":[59,100,120,139,160,167],"chance":[60,77,168],"rain":[62,170],"first":[64],"determined.":[65],"Then,":[66],"performed":[71,107],"only":[72],"if":[73],"there":[74],"rain.":[79],"As":[80,118],"outcomes,":[81],"rules":[82,162],"for":[83,165],"are":[86,133,151,163],"provided,":[87],"which":[88],"may":[89],"hidden,":[91],"but":[92],"patterns":[94],"with":[95,112,129,147],"transparent":[96],"reasons.":[97],"validate":[99],"rules,":[101],"ten-fold":[102],"cross":[103],"validation":[104],"method":[105],"its":[109],"average":[110,121,140],"accuracy":[111],"precision":[113],"recall":[115],"reported.":[117],"results,":[119],"accuracies":[122,142],"classifying":[124],"predicting":[126,166],"raining":[127],"conditions":[128],"C4.5":[132,150],"99.2%":[134],"99.3%,":[136],"respectively.":[137],"And":[138],"estimating":[144],"92.8%":[152],"93.4%,":[154],"correspondingly.":[155],"Overall,":[156],"believe":[158],"that":[159],"generated":[161],"useful":[164],"quantitatively":[172],"measuring":[173],"rainfall.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}